PetIGA

PetIGA: high-performance isogeometric analysis. This software framework implements a NURBS-based Galerkin finite element method (FEM), popularly known as isogeometric analysis (IGA). It is heavily based on PETSc, the Portable, Extensible Toolkit for Scientific Computation. PETSc is a collection of algorithms and data structures for the solution of scientific problems, particularly those modeled by partial differential equations (PDEs). PETSc is written to be applicable to a range of problem sizes, including large-scale simulations where high performance parallel is a must. PetIGA can be thought of as an extension of PETSc, which adds the NURBS discretization capability and the integration of forms. The PetIGA framework is intended for researchers in the numeric solution of PDEs who have applications which require extensive computational resources.


References in zbMATH (referenced in 43 articles , 1 standard article )

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  1. Bazilevs, Yuri; Kamensky, David; Moutsanidis, Georgios; Shende, Shaunak: Residual-based shock capturing in solids (2020)
  2. Du, Xiaoxiao; Zhao, Gang; Wang, Wei; Guo, Mayi; Zhang, Ran; Yang, Jiaming: NLIGA: a MATLAB framework for nonlinear isogeometric analysis (2020)
  3. Temizer, İ.; Motamarri, P.; Gavini, V.: NURBS-based non-periodic finite element framework for Kohn-Sham density functional theory calculations (2020)
  4. Cimrman, Robert; Lukeš, Vladimír; Rohan, Eduard: Multiscale finite element calculations in Python using sfepy (2019)
  5. Clavijo, S. P.; Sarmiento, A. F.; Espath, L. F. R.; Dalcin, L.; Cortes, A. M. A.; Calo, V. M.: Reactive (n)-species Cahn-Hilliard system: a thermodynamically-consistent model for reversible chemical reactions (2019)
  6. Garcia, Daniel; Pardo, David; Calo, Victor M.: Refined isogeometric analysis for fluid mechanics and electromagnetics (2019)
  7. Kamensky, David; Bazilevs, Yuri: \textsctIGAr: automating isogeometric analysis with \textscFEniCS (2019)
  8. Teichert, G. H.; Natarajan, A. R.; Van der Ven, A.; Garikipati, K.: Machine learning materials physics: integrable deep neural networks enable scale bridging by learning free energy functions (2019)
  9. Thai, H. P.; Chamoin, L.; Ha-Minh, C.: \textitAposteriori error estimation for isogeometric analysis using the concept of constitutive relation error (2019)
  10. Valizadeh, Navid; Rabczuk, Timon: Isogeometric analysis for phase-field models of geometric PDEs and high-order PDEs on stationary and evolving surfaces (2019)
  11. Casquero, Hugo; Zhang, Yongjie Jessica; Bona-Casas, Carles; Dalcin, Lisandro; Gomez, Hector: Non-body-fitted fluid-structure interaction: divergence-conforming B-splines, fully-implicit dynamics, and variational formulation (2018)
  12. Chávez, Gustavo; Turkiyyah, George; Zampini, Stefano; Keyes, David: Parallel accelerated cyclic reduction preconditioner for three-dimensional elliptic PDEs with variable coefficients (2018)
  13. Garcia, Daniel; Pardo, David; Dalcin, Lisandro; Calo, Victor M.: Refined isogeometric analysis for a preconditioned conjugate gradient solver (2018)
  14. Garcia, D.; Ghommem, M.; Collier, N.; Varga, B. O. N.; Calo, V. M.: PyFly: a fast, portable aerodynamics simulator (2018)
  15. Ibeid, Huda; Yokota, Rio; Pestana, Jennifer; Keyes, David: Fast multipole preconditioners for sparse matrices arising from elliptic equations (2018)
  16. Kollmannsberger, Stefan; Özcan, A.; Carraturo, Massimo; Zander, N.; Rank, E.: A hierarchical computational model for moving thermal loads and phase changes with applications to selective laser melting (2018)
  17. Pavarino, L. F.; Scacchi, S.; Widlund, O. B.; Zampini, S.: Isogeometric BDDC deluxe preconditioners for linear elasticity (2018)
  18. Pitton, Giuseppe; Heltai, Luca: NURBS-SEM: a hybrid spectral element method on NURBS maps for the solution of elliptic PDEs on surfaces (2018)
  19. Puzyrev, Vladimir; Deng, Quanling; Calo, Victor: Spectral approximation properties of isogeometric analysis with variable continuity (2018)
  20. A.F. Sarmiento, A.M.A. Cortes, D.A. Garcia, L. Dalcin, N. Collier, V.M. Calo: PetIGA-MF: A multi-field high-performance toolbox for structure-preserving B-splines spaces (2017) not zbMATH

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